# Merge Sorted Array🐧

--

You are given two integer arrays `nums1`

and `nums2`

, sorted in **non-decreasing order**, and two integers `m`

and `n`

, representing the number of elements in `nums1`

and `nums2`

respectively.

**Merge** `nums1`

and `nums2`

into a single array sorted in **non-decreasing order**.

The final sorted array should not be returned by the function, but instead be *stored inside the array *`nums1`

. To accommodate this, `nums1`

has a length of `m + n`

, where the first `m`

elements denote the elements that should be merged, and the last `n`

elements are set to `0`

and should be ignored. `nums2`

has a length of `n`

.

**Example 1:**

**Input:** nums1 = [1,2,3,0,0,0], m = 3, nums2 = [2,5,6], n = 3

**Output:** [1,2,2,3,5,6]

**Explanation:** The arrays we are merging are [1,2,3] and [2,5,6].

The result of the merge is [1,2,2,3,5,6] with the underlined elements coming from nums1.

**Example 2:**

**Input:** nums1 = [1], m = 1, nums2 = [], n = 0

**Output:** [1]

**Explanation:** The arrays we are merging are [1] and [].

The result of the merge is [1].

**Example 3:**

**Input:** nums1 = [0], m = 0, nums2 = [1], n = 1

**Output:** [1]

**Explanation:** The arrays we are merging are [] and [1].

The result of the merge is [1].

Note that because m = 0, there are no elements in nums1. The 0 is only there to ensure the merge result can fit in nums1.

**Constraints:**

`nums1.length == m + n`

`nums2.length == n`

`0 <= m, n <= 200`

`1 <= m + n <= 200`

`-109 <= nums1[i], nums2[j] <= 109`

**Follow up: **Can you come up with an algorithm that runs in `O(m + n)`

time?

# Solution

Time complexity

O(n log n)Space complexity

O(1)

Time complexity O(2 (m+n)) ->

O(m+n)Space complexity

O(m+n)

**Do you see that green follow button? 🐌**

**What if?**